Transcriptomic analysis of human blood samples to identify severity-associated markers in Plasmodium knowlesi malaria

Abstract

Malaria caused by Plasmodium knowlesi can result in non-severe or severe disease in patients. Transcriptomic-based approaches may provide deeper insights into parasite biology and host immune pathways involved in malaria severity. In our study, the blood transcriptome of P. knowlesi-infecting patients was assessed by high-throughput sequencing (RNA-seq). The expression profiles associated with clinical status were analyzed to determine the human differentially expressed genes (DEGs) and relevant pathways while the changes in leukocyte abundance were investigated using cell deconvolution. Additionally, a bioinformatics pipeline was developed to identify malaria-associated viruses and their potential impact on the severity status of this disease. We identified 362 human DEGs, which involve various mechanisms including RNA/protein metabolism and immune cell signaling. Among the identified DEGs, ALOX5 was successfully validated. Furthermore, decreased proportion of NK cells and CD8 T cells in severe samples were observed, which contributed to lymphopenia. Finally, the putative existence of six viruses was found with varying viral loads, and one of them was correlated with malaria severity. This is the first study focused on blood transcriptome and the existence of viruses in patients with P. knowlesi infection; hence, our findings may form a good basis for future research on this type of malaria.